Abstract
To improve the accuracy and acceptance of driver fatigue recognition in practical applications and vehicle safety, by comparing the driver's face expression features, car driving characteristics and other multi-source fatigue information collection and driver acceptance, a fatigue driving state recognition scheme based on multi-source information fusion is proposed. The scheme includes two cameras and a steering angle sensor. The front-up camera collects eye position, frequency of blinks, frequency of glancing, staring time, and other indicators; The side camera collects the information of driver's head position; the steering angle sensor collects the steering wheel angle data. The fatigue driving state of the driver is classified and defined by a multi-source information detection method such as pupil characteristics, head tilt angle and steering wheel angle data. Through a comparison of Test Schemes for fatigue driving, it is concluded that the simulation driving experiment scheme has the best comprehensive index in terms of safety, economics, driving state fit and so on. Based on the work above, an experimental platform for fatigue driving recognition was established.
Highlights
Traffic acc idents are one of the serious social proble ms in the world
According to the World Health Organization (WHO), casualties caused by road traffic accidents by 2030 will be one of the main causes of human death and injury
There are at least 100,000 traffic accidents caused by fatigue driving in the United States each year, and 10% o f accidents caused by fatigue driving in traffic accidents in the Un ited Kingdom
Summary
Traffic acc idents are one of the serious social proble ms in the world. According to the World Health Organization (WHO), casualties caused by road traffic accidents by 2030 will be one of the main causes of human death and injury. According to statistics on traffic accidents in many countries, fatigue driv ing is one of the most important causes of traffic accidents (1). Accidents caused by fatigue driving account for 20.6% of casualties in France. The research on drivers fatigue detection is of great significance. Many countries have begun research and development of fatigue driving detection and Driver Fat igue Monitor System. Chinese research on fatigue driving started late. The JLUVA-DFWS system developed by Jilin Un iversity infers the driver's mental state based on eye and lip opening, and give warn ing message if the driver appears fatigue state during driv ing. The acceptance of the testing equipment by the driver in practical applications is not taken into account in the current fatigue detection research. This paper studies the fatigue driving state based on mu lti-source Information fusion.
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